Experience

• Designing and developing IT-based conceptual models to optimize supply chain.

• Performing quantitative data analysis using Python, applying statistical modeling and data visualization to evaluate supply chain performance metrics.

• Utilizing NVivo for qualitative data analysis, including thematic coding and content analysis from interviews, focus groups, and case studies with industry stakeholders.

• Integrating mixed-methods research to ensure comprehensive analysis and insights from both structured and unstructured data sources.

• Collaborating with academic advisors, IT experts, and supply chain professionals to align theoretical research with practical, industry-relevant solutions.

• Preparing reports, academic publications, and conference presentations to disseminate research findings.

Project: Transforming Novice Driver Training in Bangladesh: Integrating Technology for Safer Roads.

• Led a structured action research initiative aimed at modernizing novice driver training by integrating essential digital tools and technology-based learning modules.

• Designed and implemented IT-based training modules, successfully training over 300 novice drivers and driving instructors through a series of interactive, hands-on sessions.

• Conducted field-level research involving 150 professional drivers and consultations with 10 transportation and education experts (including BRTA officials, traffic personnel, and university researchers) to identify key technologies critical to daily driving in Bangladesh.

• Identified and integrated seven core technologies—including GPS navigation, ride-sharing apps, BRTA digital services, e-Toll systems, online GDs, helpline tools, and road crash databases—into the training framework.

• Collaborated with key stakeholders including BRTC and other driving schools to standardize content delivery and ensure alignment with national transportation policies.

Training Implementation Highlights:

• Organized 7 training sessions at driving training centers:

  • 6 sessions for novice drivers (approximately 300 participants) in three progressive stages based on feedback and demand.

  • 1 master training session for driving instructors to ensure scalability and future training continuity.

Data Collection & Analysis:

• Collected survey and interview data from participants to assess technology adoption, confidence, and training impact.

• Applied descriptive statistical methods using SPSS and Microsoft Excel, including:

o Frequency and percentage distribution

o Mean and standard deviation calculations

o Visualization with bar charts, pie charts, radar charts, and histograms to present findings clearly.

Outcome:

• Developed a replicable, scalable driver training model integrating digital literacy.

• Authored 2 journal articles based on field research and training phases (currently under peer review).

Topic: Customer Webrooming Behavior in Consumer Electronics Industry of Bangladesh.

• Collected and analyzed data from approximately 400 respondents using convenient sampling with judgment, ensuring targeted and contextually relevant insights.

• Designed and distributed structured questionnaires to capture key behavioral patterns and customer motivations.

• Employed SPSS for comprehensive quantitative data analysis, including:

1. Cronbach’s Alpha for testing reliability of measurement scales

2. Pearson’s Correlation Analysis to assess relationships among variables

3. Multiple Regression Analysis to determine the impact of independent variables on dependent outcomes ('Search Online' and 'Purchase Offline')

• Interpreted results to identify core factors influencing online research and offline purchase behavior, contributing to actionable insights for retailers and marketers.

• Applied findings to suggest strategic improvements in omnichannel retailing and supply chain alignment in the electronics industry.

Outcome: Two peer-reviewed publications, one focusing on Online Search Factors and the other on Purchase Offline Factors.